Measuring Pitchers’ Performance Using Data Envelopment Analysis with Advanced Statistics

Abstract

This paper evaluates starting pitchers’ pitching performance during the 2008 to 2014 Major League Baseball (MLB) seasons. We use data envelopment analysis (DEA) based on two inputs (i.e., innings pitched [IPs] and per pitched innings) and three outputs (fielding independent pitching, earned run average [ERA], and skill-interactive ERA) to evaluate the performance of the 30 MLB teams’ starting pitchers with IPs greater than 200 in each single season (2008 to 2014, regular season only). We used the CCR models to calculate the overall efficiency, scale efficiency, technical efficiency, efficiency value, and the slack analysis to measure a pitcher’s performance in each single season. The results showed that 4, 3, 4, 3, 5, 3, and 5 pitches reached overall efficiency each year, from 2008 to 2014 (regular season). By analyzing the results and computing performance indexes and benchmarks for each starting pitcher, we determine the true value of each player to help baseball teams select highly indexed players and maximize player efficiency. Keywords: Advanced Statistics, Pitchers, Data Envelopment Analysis, Innings Pitched, Earned Run Average  
 
Corresponding author: Huichin Wu (elaine@mail.ntpu.edu.tw).  
 
To cite this document:  
Shihteng Chiu, Chiahuei Hsiao, and Huichin Wu, "Measuring Pitchers’ Performance Using Data Envelopment Analysis with Advanced Statistics", Contemporary Management Research, Vol.11, No.4, pp. 351-384, 2015.  
Permanent link to this document: http://dx.doi.org/10.7903/cmr.14157